Introduction

Mental health disabilities have emerged as the predominant disability group across post-secondary institutions in the United States. In fact, NPSAS data suggests that the significant increase in university enrollments from students with disabilities over the last two decades is largely driven by this disability group (2020 GAO data). Estimates vary on the prevalence of this disability group within institutions: UCUES 2025 [30% of all students while 54% reported learning], however UCUES 2022 data was different [39% of all disabilities were MH; 4% learning]; Univeristy of Texas, Austin 2024 [2157/3885=55.5%; learning only 16%]; UC Berkeley April 2025 [2513/5680=44%; learning only 5%]; Syracuse University 2024 [students may report more than one: 41% mental health ;74.1% learning (includes ADHD)]; University of Oregon 2023 [27.3% MH; 16% ADHD/learning]. A significant contribution to the variability in prevalence estimates is due to the variability in the definition of what constitutes a mental health disability to researchers, how disability service offices determine eligibility for disabilities, and the use of self-report data from students themselves. For the purpose of this study, we adhere to the ADA definition of psychiatric (mental health) disabilities as: “a mental impairment that substantially limits one or more of the major life activities of [an] individual; a record of impairment; or being regarded as having such an impairment.”

Service access

Compared to other disability groups, the rising prevalence of mental health disabilities has unique consequences for service provision within institutions whereby there is an increased demand for both mental health treatment through counselling and psychological services (CAPS) and disability management through disability service offices (DSO). In this context, it is estimated that a majority of students with mental health disabilities (SMHDs) do not receive accommodations, which may be a significant contributor to poorer mental health, social and academic outcomes for these students.

Felber et al., 2020 reported on 2016/2017 data that 86.7% of SMHDs in their sample who qualified for a mental health disability under the ADA reported to not having registered for accommodations. Similarly, UC systems data from 2020 and 2022 indicated that 18% and 27% of students with mental health concerns/disorders received accommodations, respectively. More recent data (Barnard-Brak 2022) has estimated that approximately 59% of students (n=3593) with psychological disorders were not registered for accommodations while our data suggests that this is now 69%. Interestingly, in this 2023/24 sample there were 16264 students who reported diagnosed psychological disorders, so while the proportion of students with psychological disorders registering with DSOs has fallen, the total number of students registered with DSOs has increased almost three-fold. This may be a result of a reduction in the availability of services, an increase in barriers to accessing these services (stigma, infrastructural, perceived need), or that the increased percentage of students reporting mental health disorders are presenting with ‘milder’ symptoms/fewer functional limitations.

One limitation with the Felber study is the claim that participants who reported that they had been diagnosed with a mental health disorder by a health professional thus qualified under ADA for a mental health disability. A mental health disorder diagnosis does not automatically qualify as a disability without evidence of functional limitation; a proportion of the students included in this group would not report functional limitations due to their disability. This figure of 86.7% is very likely an underestimation of the proportion of SMHDs who registered for accommodations by including students who likely are unlikely to meet the critera of disability. As we will argue later, it is much more useful to constrain this sample to those disagnosed with a mental health disorder who also report SEVERE symptoms, which is strongly correlated with functional limitations

Ultimately, the common, persistent challenge with estimating the prevalence and service access underutilization for this cohort is the lack of data on functional limitations associated with student’s reporting mental health disorders. This gap makes it difficult to infer on whether a reported mental health disorder ‘elevates’ to the level of disability, which impacts an institution’s ability to allocate resources based on the needs of its students. National surveys such as the BRFSS, NHANES and the NHIS all inquire about the functional limitations alongside specific diagnoses of chronic diseases and mental health disorders. As it is already an integral part how disability service offices assess students during accommodation interviews, collection of these data alongside mental health diagnoses can better triangulate the numbers and severity of students with mental health disorders who receive accommodations within universities. Despite the gap in prevalence and service utilization data, one well-established predictor of service access for students with disabilities is stigma.

Stigma

Understanding the role of disability stigma in service access for students with disabilities is critical considering it is well-established that there are differential service access rates dependent on sociocultural factors of students and the types of institutions they attend (Weis & Brittner, 2022). If students from disadvantaged gender, cultural or economic groups are more likely to experience stigma due to their disability then this will have a differential impact on how these groups access university services This is a significant equity issue in research into service access for students with disabilities whereby early intervention into stigma may disproportionately improve access for those who need the most support. Despite this, there have been few investigations into the role of stigma, be it mental health or disability stigma, and service access for students with disabilities in post-secondary education.

Previous studies have described the important role that stigma plays in self-disclosure and service access for students with disabilities. Barnard-Brak et al., 2009 reported that students who did not accept their disability were less likely to request accommodations; Marshak et al., 2010 reported from qualitative data that disability stigma was a barrier for students with disabilities in accessing accommodations. For those with mental health “issues”, internalized/personal stigma was a barrier to seeking academic support and self-disclosure more broadly (Grimes 2020). For students with learning disabilities, nagative views of their disability and concerns about how other students, staff or faculty may respond to their disability negatively impacted their decision to self-disclose (Cole et al., 2015). Felber at al., 2020 explored differences in mental health treatment access between SMHDs who were and were not registered to DSOS, which showed small effect sizes for the negative association between perceived stigma and mental health treatment access. To this author’s knowledge, no study has quantiatively investigated the association between stigma and disability service access in SMHDs. Barnard-Brak et al., 2020 reported positive associations between receiving therapy or taking medication (for mental health reasons), and registering with DSOs, however stigma was not included in their model.

This study aims to fill the gap in the service access and disability literature by exploring the association between stigma (personal and perceived) and service access (registering with DSOs or receiving mental health treatment) for students with psychological/mental health disabilities. Importantly, we build-on prior work by using a new HealthyMinds Study self-reported disability group question (‘Do you have a disability, or disabilities, from any of the following categories?’), as opposed to the prior year’s question asking. Older HMS datasets queried disability status by asking what disability a student received an accommodation for, which constrained the entire sample of students with disabilities to those who received accommodations. Conversely, other analyses were limited by assuming that those with a diagnosed mental health disorder could be counted as those with a mental health disability, which is not necessarily true.

This analysis defines disability by combining self-identification of a disability with self-reported diagnosis of a mental health disorder, meaning our sample is unconstrained by registration with disability service office. This allows us to assess prevalences and differences in accommodation access in relation to presence of stigma for students with psychological disabilities. Of note, our models incorporate mental health stigma rather than disability stigma (could be a measure like the PSSDS), which would be a novel testing of the relationship between mental health and disability management for this group [the only stigma measure available in the HMS dataset was the mental health stigma]. Few [perhaps no one?] have explored perceptions of students with mental health disorders and contextualizing their experiences within a conceptual model of disability. This study aims to elucidate a relationship between mental health disorders, disability and the role of stigma in mediating university student access to support services.

Table 1 - Characterstics of weighted sample by disability type

Characteristic Total1 None, N = 120,6411 Attention deficit/hyperactivity disorders, N = 17,9751 Deaf or hard of hearing, N = 1,4651 Learning disorders, N = 3,1321 Mobility impairments, N = 6541 Neurological disorders, N = 1,6171 Physical/health related disorders, N = 5,0801 Psychological disorder/condition, N = 2,4821 Visual impairments, N = 8,0691 Other (please specify), N = 14,1231 Multiple disabilities, N = 20,1651
Age 21 (8) 21 (8) 22 (7) 22 (12) 21 (8) 27 (12) 21 (8) 21 (10) 22 (9) 20 (7) 21 (8) 22 (10)
Gender











    Male 80,602 (41%) 49,949 (42%) 8,179 (46%) 711 (49%) 1,060 (34%) 318 (49%) 621 (39%) 1,480 (29%) 569 (23%) 3,660 (45%) 6,591 (47%) 7,465 (37%)
    Female 107,182 (55%) 67,535 (56%) 8,884 (50%) 720 (49%) 1,909 (61%) 284 (43%) 888 (55%) 3,422 (68%) 1,723 (70%) 4,096 (51%) 7,193 (51%) 10,527 (52%)
    Genderqueer 1,560 (0.8%) 513 (0.4%) 217 (1.2%) 3 (0.2%) 33 (1.0%) 2 (0.3%) 37 (2.3%) 40 (0.8%) 27 (1.1%) 50 (0.6%) 49 (0.3%) 591 (2.9%)
    Non-binary 1,886 (1.0%) 726 (0.6%) 264 (1.5%) 2 (0.1%) 22 (0.7%) 7 (1.0%) 27 (1.7%) 47 (0.9%) 53 (2.1%) 70 (0.9%) 58 (0.4%) 611 (3.0%)
    Transgender 500 (0.3%) 121 (0.1%) 51 (0.3%) 1 (<0.1%) 35 (1.1%) 25 (3.8%) 4 (0.2%) 11 (0.2%) 14 (0.6%) 28 (0.4%) 26 (0.2%) 185 (0.9%)
    Prefer not to respond 2,169 (1.1%) 832 (0.7%) 279 (1.6%) 19 (1.3%) 51 (1.6%) 13 (2.0%) 27 (1.7%) 57 (1.1%) 64 (2.6%) 90 (1.1%) 98 (0.7%) 639 (3.2%)
    Self-identified 1,054 (0.5%) 631 (0.5%) 72 (0.4%) 10 (0.7%) 20 (0.6%) 5 (0.8%) 9 (0.5%) 11 (0.2%) 14 (0.6%) 68 (0.8%) 88 (0.6%) 126 (0.6%)
    Unknown 449 334 30 0 1 0 4 12 18 7 20 21
Race/Ethnicity











    Black 29,970 (15%) 18,676 (16%) 2,157 (12%) 127 (8.6%) 466 (15%) 89 (14%) 180 (11%) 708 (14%) 249 (10%) 1,447 (18%) 3,884 (28%) 1,988 (9.9%)
    AI/AN 3,707 (1.9%) 1,974 (1.6%) 336 (1.9%) 57 (3.9%) 90 (2.9%) 28 (4.3%) 49 (3.0%) 103 (2.0%) 64 (2.6%) 133 (1.7%) 243 (1.7%) 629 (3.1%)
    Asian 16,494 (8.5%) 11,331 (9.5%) 1,129 (6.3%) 82 (5.6%) 183 (5.8%) 21 (3.3%) 78 (4.8%) 254 (5.0%) 157 (6.3%) 749 (9.3%) 1,611 (11%) 900 (4.5%)
    Hispanic/Latinx 24,495 (13%) 15,892 (13%) 1,844 (10%) 176 (12%) 361 (12%) 51 (7.8%) 125 (7.7%) 428 (8.4%) 271 (11%) 1,144 (14%) 2,361 (17%) 1,842 (9.2%)
    NH/PI 570 (0.3%) 361 (0.3%) 40 (0.2%) 9 (0.6%) 6 (0.2%) 3 (0.5%) 1 (<0.1%) 23 (0.5%) 3 (0.1%) 28 (0.3%) 36 (0.3%) 58 (0.3%)
    Middle Eastern 2,504 (1.3%) 1,552 (1.3%) 384 (2.1%) 9 (0.6%) 22 (0.7%) 13 (2.0%) 12 (0.7%) 66 (1.3%) 27 (1.1%) 67 (0.8%) 179 (1.3%) 172 (0.9%)
    White 114,599 (59%) 68,862 (58%) 11,945 (67%) 984 (67%) 1,959 (63%) 432 (66%) 1,167 (72%) 3,448 (68%) 1,662 (67%) 4,387 (55%) 5,529 (39%) 14,225 (71%)
    Self-identified 1,993 (1.0%) 1,091 (0.9%) 121 (0.7%) 20 (1.4%) 39 (1.2%) 16 (2.4%) 6 (0.4%) 34 (0.7%) 44 (1.8%) 92 (1.1%) 244 (1.7%) 286 (1.4%)
    Unknown 1,072 901 20 1 6 0 0 16 5 23 36 64
PHQ-9 score 8 (6) 7 (6) 9 (6) 7 (6) 8 (6) 9 (6) 9 (6) 9 (6) 11 (7) 7 (6) 6 (6) 12 (7)
    Unknown 18,572 16,601 462 29 84 21 39 140 74 191 510 422
GAD-7 score 7 (6) 6 (6) 8 (6) 6 (6) 7 (6) 7 (6) 8 (6) 8 (6) 11 (6) 6 (6) 5 (6) 10 (6)
    Unknown 18,696 17,236 289 39 63 6 35 69 36 211 411 302
1 Median (SD); n (%)

Students who self-ID as having a psychological disability

In this dataset, mental health disability is represented by a variable called disab_1_7 that is one of a list of 9 disability types that students can select if it applies to them.

Respondents are asked: Do you have a disability, or disabilities, from any of the following categories? (Select all that apply): Psychological disorder/condition.

I will use this section to explore the prevalence of these students and their uniqueness compared to other groups; I will present a few datapoints to explore these students within this dataset.

Psychological Disability Overview:

  • 92.4% of students who report a psychological disability also report a depressive or anxiety disorder.
  • 38% of students who report a psychological disability also report ADHD.
  • 36.9% of students who report a psychological disability receive accommodations (note: this may be for a co-occurring disability such as ADHD or vision impairment).

ONLY those who report psychological disability who receive accommodations.

In order to get a better appreciation of how mental health/psychological disability may be impacting disability service access, it is important to remove potential counfounding from other disability groups. Using the ‘psychological disability’ variable as is will also include students who have selected other disabilities, which may mean the mental health disability arose secondarily to a ‘primary’ disability, which is common in this population. In our case, it is useful to constrain our dataset to those who ONLY report a mental health disability absent of another. Further, we consider ‘registering with disability service office’ as a proxy for accessing academic accommodations.

I perform two steps: 1) I construct a dataframe restricted to those who ONLY reported psychological disabilities; 2) Perform quality control by removing those who did not also report a mental health diagnosis from a professional (that would exclude them from having a possible psychological/mental health disability). This accounted for ~5% of the subsample.

Percentage of students who report only psychological disability and have a mental health disorder diagnosis:

  • 94.9% of students who report only a psychological disability also report a mental health diagnosis.

Percentage of students who report only psychological disability and have a mental health disorder diagnosis who are registered with their disability service office:

  • 27.8% of these students receive accommodations.

It is also important to explore how students who only identify as having a psychological/mental health disability with a mental health diagnosis differ from the general population of those that report mental health diagnosis without a psychological/mental health disability.

I will use two mental health outcomes measures to explore this: PHQ9, GAD7.

Median PHQ-9 and GAD-7 Scores by Group:

  • Median PHQ-9 score (All with MH diagnosis): 10

  • Median PHQ-9 score (MH diagnosis, no psychological disability): 10

  • Median PHQ-9 score (Only psychological/mental health disability): 12

  • Median GAD-7 score (All with MH diagnosis): 9

  • Median GAD-7 score (MH diagnosis, no psychological disability): 9

  • Median GAD-7 score (Only psychological/mental health disability): 11

This makes sense: a big difference between those with MH disorder and those with only Psych/MH disabilities is the severity of symptoms i.e., those with psych disabilities describe more severe mental health symptoms than those who report.

This leads us to consider the association between the severity of symptoms and disability, which should be mechanistically connected by the impact symptom severity has on functional limitations. Recent NHANES data demonstrated exactly this (Meshkate et al., 2025): a strong positive association between depressive symptoms as measured by the PHQ9 and functional limitations as measured by the Disability Questionnaire (measures based on activities of daily living).

Functional limitations and disability

In this context, those reporting severe symptoms from a mental health diagnosis are likely to also report functional limitations, which would qualify them as having a disability. We can first explore this within our own data using bespoke functional limitations equivalent measures included in our dataset (dep_imp & gad7_impa), which asks: “How difficult have these problems (noted above) made it for you to do your work, take care of things at home, or get along with other people?” This prompts a 4-point Likert scale response from Not at all difficult –> Extremely difficult.

## **Proportion of Students with Diagnosed MH Disorder and Severe Symptoms Who Report Functional Limitations**
Functional Limitation Status Proportion
Without limitations 0.256
With limitations 0.744
## **Breakdown of Psychological Disability Reporting by Functional Limitation Status**
Functional Limitation Status Psychological Disability Reporting Proportion
Without limitations Reports psych disability 0.028
Without limitations Missing 0.228
With limitations Reports psych disability 0.137
With limitations Missing 0.607
## **Proportion of Students with MH Diagnosis and Functional Limitations Who Report Psychological Disability**
Psychological Disability Reporting Proportion
Reports psych disability 0.184
Missing 0.816
##   selectedotherdisability total
## 1                    5057  9252

Firstly, for those with both a MH diagnosis AND severe depressive or anxiety symptoms 74% report functional limitations as a result of these symptoms. Of those, only 14% reported a psychological/mental health disability and 61% did not. 3% of those without functional limitation reported a psychological/mental health disability. Relatedly, 15% of students with both a MH diagnosis AND severe depressive or anxiety symptoms who reported receiving accommodations do not report any functional limitations.

Secondly, 82% of those with a MH diagnosis who reported severe depressive or anxiety symptoms that caused functional limitations do NOT report having a psychological disability. This represents a significant proportion of this sample who would be considered having a psychologica/mental health disability but do not self-identify as having one.

Of this 82%, 61% identify a non-psychological disability and so may consider the functional limitations they experience due to depression/anxiety a result of their ‘primary’ disability, not a psychological disability. Despite this, a significant number of students with non-psychological disabilities DO co-report a psychological/mental health disability in the presence of functional limitations related to depression/anxiety, so it is unlikely entirely explained by this.

This does however, beg the question: is a mental health disorder/condition, which arises due to another disability (ADHD, dyslexia, specific learning disability) that students report as leading to functional limitations simply a symptom of their original disability, or is it its own disability? If the latter, how does this impact care? Perhaps disability care focuses on managing the functional limitations associated with the original disability (which MAY be different to the pyschological disability) with the intention that downstream it will benefit the psychological/mental health disability. Perhaps disability care providers consider the management of the mental health disorders that arise from another disability within the purview of mental health providers/clinicians. The remains a lack of clarity in the management of ‘secondary’ psychological/mental health disabilities.

Regardless, 40% of those with functional limitations from depression or anxiety who do not report ANY other disability, also do not report a psychological disability. This leads us to our most conservative estimate that 4/10 students who report functional limitations due to severe mental health symptoms who are also not receiving disability care for a non-psychological disability do not self-identify as having a psychological disability despite their eligibility.

This may be a result of unmeasured disability stigma in this group where students may recognize their mental health disorder as disabling however, feel uncomfortable linking this to a pyschological disability. It may also be a result of a lack of disability cultural competency where these students do not recognize that their mental health disorder, which is causing significant limitations in their daily activities (such as socializing or studying, attending class etc) is disabling and thus, they have a disability.

It may also relate to the use of the term pyschological instead of mental health: students may be not understand that depressive or anxiety disorders are a psychological disorder/condition since mental health is the most common parlance for these terms currently. This speaks to the importance of language in the assessment, communication and delivery of disability care for these students, particularly those across different sociiocultural and linguistic backgrounds.

An important caveat to these data regarding unmet care needs is that respondents are required self-identify as having a disability before they can select whether they are registered with a disability service office (proxy for receiving accommodations). It is possible that there is a cohort within this sample who reported severe depressive or anxiety symptoms that caused functional limitations, who do NOT report having a psychological disability but DO receive accommodations. This would mean that they are having their disability care needs met despite not reporting a psychological disability (possibly for a different disability).

Disability Self-ID, Stigma and Functional limitation models

So, now that we understand the extent that severe dep/anx symptoms relate to functional limitations in this population of students with mental health diagnoses, and that a report of functional limitations due to their depression/anxiety is unlikely to mean that a student identifies as having a psychological disability. This begs the question: what might be the mechanism by which a student with mental health diagnoses and severe symptoms chooses to self-identify as having a psychological disability or not?

A priori evidence suggests that stigma may be an important factor here, particularly when comparing those who report a functional limitation vs those who do not. I will run two regression with interactions between stigma (personal then perceived) and report of functional impairment (yes or no) to explore how this impacts the probability of a student with a mental health diagnoses and severe dep/anx symptoms self-identifying as having a psychological disability.

For our analyses, we only have access to mental health stigma (personal, perceived and stigma of seeking mental health treatment), not disability stigma. For students with psychological/mental health disabilities, it is likely that mental health stigma interacts with disability stigma in ways that it does not for other disability groups; in this context, would mental health stigma and disability stigma be measuring different constructs? It is possible the answer to this question is yes however, I believe there would be a strong correlation between the two.

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From these data, there is no interaction effect of stigma between those who or do not report a functional limitation and our outcome. Increasing personal and self stigma described an association with lower probability of self-identifying as having a psychological disability for those who do and do not report functional limitations. In fact, those with the lowest personal stigma scores who reported a functional limitation were almost four times more likely to self-identify a psychological disability than those with the highest stigma score (note: low basline or self-ID!). The difference between lowest and highest for help-seeking stigma scores was just under double the probability for self-identify with a psychological disability in both groups.

Perceived mental health stigma described the opposite association: higher perceived mental health stigma resulted in higher probability of self-identifying with a psychological disability. I do not know why this would be!

These data are is critical as self-identification is a pre-requisite to accessing disability care in post-secondary education e.g., students need to self-disclose their disability to receive accommodations from disability service offices. If stigma is preventing self-disclosure of a disability, ipso facto stigma is preventing access to disability care. For those who do not report a functional limitation this may not be significant as they, according to the accepted ADA definition of disability, would not be eligible for disability care. However, for those who do report functional limitations, this is significant!

Stigma and access to disability services models

We have established an association between stigma and self-identification of psychological disability however, how does stigma also impact a student who HAS self-ID’d and their subsequent self-DISCLOSURE to DSO or mental health services? In these models, we constrain our sample to those who ONLY reported a psychological disability to avoid biasing our sample with those who may have received care for a co-occuring disability. We also condition our sample on those who report a mental health diagnosis.

Stigma and DSO/Therapy Last 12 months plots

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Limitations

Perhaps disability stigma is modified by an unmeasured confounder that causes a subset of students with a diagnosed mental health diagnosis to not self-report a disability, biasing our results. This could be socioeconomic factors, type of secondary school institution, family income etc.

Stigma measures: Eisenberg et al., 2009 (https://websites.umich.edu/~daneis/papers/hmpapers/Stigma%20_Eisenberg%20et%20al%202009_.pdf)